Because of the extremely complexed microenvironment of drug-resistant bacterial infection, nanomaterials with both bactericidal and immuno-modulating activities are undoubtedly the ideal modality for overcoming drug resistance. Herein, we precisely engineered the surface chemistry of selenium nanoparticles (SeNPs) using neutral (polyvinylpyrrolidone-PVP), anionic (letinan-LET) and cationic (chitosan-CS) surfactants. It was found that surface chemistry greatly influenced the bioactivities of functionalized SeNPs, their interactions with methicillin-resistant Staphylococcus aureus (MRSA), immune cells and metabolisms. LET-functionalized SeNPs with distinct metabolisms exhibited the best inhibitory efficacy compared to other kinds of SeNPs against MRSA through inducing robust ROS generation and damaging bacterial cell wall. Meanwhile, only LET-SeNPs could effectively activate natural kill (NK) cells, and enhance the phagocytic capability of macrophages and its killing activity against bacteria. Furthermore, in vivo studies suggested that LET-SeNPs treatment highly effectively combated MRSA infection and promoted wound healing by triggering much more mouse NK cells, CD8+ and CD4+ T lymphocytes infiltrating into the infected area at the early stage to efficiently eliminate MRSA in the mouse model. This study demonstrates that the novel functionalized SeNP with dual functions could serve as an effective antibacterial agent and could guide the development of next generation antibacterial agents.

Crystalline metal-organic frameworks (MOFs) have garnered extensive attention owing to their highly ordered porous structure and physicochemical properties. However, their practical application often requires their integration with various substrates, which is challenging because of their weakly adhesive nature and the diversity of substrates that exhibit different properties. Herein, we report the use of amorphous metal-phenolic network coatings to facilitate the growth of crystalline MOF coatings on various particle and planar substrates. Crystalline MOFs with different metal ions and morphologies were successfully deposited on substrates (13 types) of varying sizes, shapes, and surface chemistries. Furthermore, the physicochemical properties of the coated crystalline MOFs (e.g., composition, thickness) could be tuned using different synthesis conditions. The engineered MOF-coated membranes demonstrated excellent liquid and gas separation performance, exhibiting a high H2 permeance of 63200 GPU and a H2/CH4 selectivity of 10.19, likely attributable to the thin nature of the coating (~180 nm), which can be realized using the present strategy. Considering the vast array of MOFs available (>90,000) and the diversity of substrates, this work is expected to pave the way for creating a wide range of MOF composites and coatings with potential applications in biomedicine, environmental science, and agriculture.

Targeted nanoparticles have been extensively explored for their ability to deliver their payload to a selective cell population while reducing off-target side effects. The design of actively targeted nanoparticles requires the grafting of a ligand that specifically binds to a highly expressed receptor on the surface of the targeted cell population. Optimizing the interactions between the targeting ligand and the receptor can maximize the cellular uptake of the nanoparticles and subsequently improve their activity. Here, we evaluated how the density and presentation of the targeting ligands dictate the cellular uptake of nanoparticles. To do so, we used a DNA-scaffolded PLGA nanoparticle system to achieve efficient and tunable ligand conjugation. A prostate-specific membrane antigen (PSMA) expressing a prostate cancer cell line was used as a model. The density and presentation of PSMA targeting ligand ACUPA were precisely tuned on the DNA-scaffolded nanoparticle surface, and their impact on cellular uptake was evaluated. It was found that matching the ligand density with the cell receptor density achieved the maximum cellular uptake and specificity. Furthermore, DNA hybridization-mediated targeting chain rigidity of the DNA-scaffolded nanoparticle offered ∼3 times higher cellular uptake compared to the ACUPA-terminated PLGA nanoparticle. Our findings also indicated a ∼ 3.7-fold reduction in the cellular uptake for the DNA hybridization of the non-targeting chain. We showed that nanoparticle uptake is energy-dependent and follows a clathrin-mediated pathway. Finally, we validated the preferential tumor targeting of the nanoparticles in a bilateral tumor xenograft model. Our results provide a rational guideline for designing actively targeted nanoparticles and highlight the application of DNA-scaffolded nanoparticles as an efficient active targeting platform.

Manipulating water evaporation dynamics is a prerequisite in various modern-day applications like DNA stretching, rapid disease diagnostics, and inkjet printing. One method to affect the evaporation dynamics of droplets is to externally apply electric fields. However, surfaces that bear an intrinsic surface charge have not yet been investigated with respect to their evaporation behavior. In this study, we investigate water droplet evaporation on lithium niobate (LN), a ferroelectric material with a very high spontaneous polarization of 0.7 C/m2. Our results show that a droplet deposited on a LN surface evaporates in three stages: (i) constant contact radius (ii) mixed phase (iii) stick-slip, which is likely originating from the intrinsic surface charge. The influences of the polarization direction of the LN surface as well as the relative humidity of the environment on various evaporation characteristics were studied. The results suggest that the specific adsorption layers forming on charged surfaces, e.g. from the humidity of the surrounding air, play a key role in the evaporation process. Furthermore, compared to other materials with similar contact angles, LN demonstrated a significantly large evaporation rate. This property might also be attributed to the intrinsic surface charge and could be exploited in heat transfer applications.

Laser synthesis and processing of colloids (LSPC) is an established method for producing functional and durable nanomaterials and catalysts in virtually any liquid of choice. While the redox reactions during laser synthesis in water are fairly well understood, the corresponding reactions in organic liquids remain elusive, particularly because of the much greater complexity of carbon chemistry. To this end, this article first reviews the knowledge base of chemical reactions during LSPC and then deduces identifiable reaction pathways and mechanisms. This review also includes findings that are specific to the LSPC method variants laser ablation (LAL), fragmentation (LFL), melting (LML), and reduction (LRL) in organic liquids. A particular focus will be set on permanent gases, liquid hydrocarbons, and solid, carbonaceous species generated, including the formation of doped, compounded, and encapsulated nanoparticles. It will be shown how the choice of solvent, synthesis method, and laser parameters influence the nanostructure formation as well as the amount and chain length of the generated polyyne by-products. Finally, theoretical approaches to address the mechanisms of organic liquid decomposition and carbon shell formation are highlighted and discussed regarding current challenges and future perspectives of LSPC using organic liquids instead of water.

Polymer coating to substrates alters surface chemistry and imparts bulk material functionalities with a minute thickness, even in nanoscale. Specific surface modification of a substate usually requires an active substrate that, e.g., undergoes a chemical reaction with the modifying species. Here, we present a generic method for surface modification, namely, solid-state adsorption, occurring purely by entropic strive. Formed by heating above the melting point or glass transition and subsequent rinsing of the excess polymer, the emerging ultrathin (<10 nm) layers are known in fundamental polymer physics but have never been utilized as building blocks for materials and they have never been explored on soft matter substrates. We show with model surfaces as well as bulk substrates, how solid-state adsorption of common polymers, such as polystyrene and poly(lactic acid), can be applied on soft, cellulose-based substrates. Our study showcases the versatility of solid-state adsorption across various polymer/substrate systems. Specifically, we achieve proof-of-concept hydrophobization on flexible cellulosic substrates, maintaining irreversible and miniscule adsorption yet with nearly 100% coverage without compromising the bulk material properties. The method can be considered generic for all polymers whose Tg and Tm are below those of the to-be-coated adsorbed layer, and whose integrity can withstand the solvent leaching conditions. Its full potential has broad implications for diverse materials systems where surface coatings play an important role, such as packaging, foldable electronics, or membrane technology.

Zirconium-based metallic glasses (Zr-MGs) are demonstrated to exhibit high mechanical strength, low elastic modulus and excellent biocompatibility, making them promising materials for endosseous implants. Meanwhile, tantalum (Ta) is also well known for its ideal corrosion resistance and biological effects. However, the metal has an elastic modulus as high as 186 GPa which is not comparable to the natural bone (10-30 GPa), and it also has a relative high cost. Here, to fully exploit the advantages of Ta as endosseous implants, a small amount of Ta (as low as 3 at. %) was successfully added into a Zr-MG to generate an advanced functional endosseous implant, Zr58Cu25Al14Ta3 MG, with superior comprehensive properties. Upon carefully dissecting the atomic structure and surface chemistry, the results show that amorphization of Ta enables the uniform distribution in material surface, leading to a significantly improved chemical stability and extensive material-cell contact regulation. Systematical analyses on the immunological, angiogenesis and osteogenesis capability of the material are carried out utilizing the next-generation sequencing, revealing that Zr58Cu25Al14Ta3 MG can regulate angiogenesis through VEGF signaling pathway and osteogenesis via BMP signaling pathway. Animal experiment further confirms a sound osseointegration of Zr58Cu25Al14Ta3 MG in achieving better bone-implant-contact and inducing faster peri-implant bone formation.

Surgical ASTM F139 stainless steel is used for temporary fixtures in the biomedical field. Tribocorrosion is a major concern in this application. The aim of the present work was to study the interplay between tribocorrosion behavior and the surface chemistry of the ASTM F139 stainless steel in phosphate-buffered saline solution (PBS). Sliding wear tests were conducted against alumina balls at different electrochemical potentials: open circuit potential (OCP), cathodic potential (-100 mV versus the OCP), and anodic potentials (+200 mVAg/AgCl and +700 mVAg/AgCl). The normal load was 20 N. The wear volume was estimated based on micrographs obtained from the wear tracks using confocal laser scanning microscopy. Moreover, the wear tracks were also examined by scanning electron microscopy (SEM). The surface chemistry of the ASTM F139 specimens was analyzed by X-ray photoelectron spectroscopy (XPS). The wear volume was dependent on the electrochemical potential, being maximized at +700 mVAg/AgCl. Delamination areas and grooves were observed in the wear tracks. Detailed assessment of the surface chemistry inside the wear tracks allowed identification of the main chemical species and their relative quantities, thus enabling correlation of the passive film composition with the observed tribocorrosion behavior.

In this work, the transformation of waste iron cans to gamma iron oxide (γ-Fe2O3) nanoparticles following acid leaching precipitation method along with their structural, surface chemistry, and magnetic properties was studied. Highly magnetic iron-based nanomaterials, maghemite with high saturation magnetization have been synthesized through an acid leaching technique by carefully tuning of pH and calcination temperature. The phase composition and crystal structure, surface morphology, surface chemistry, and surface composition of the synthesized γ-Fe2O3 nanoparticles were explored by X-ray diffraction (XRD), Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS) and Energy-dispersive X-ray spectroscopy (EDS). The XRD results confirm the cubic spinel structure having crystallite size 26.90-52.15 nm. The XPS study reveals the presence of Fe, O element and the binding energy of Fe (710.31 and 724.48 eV) confirms the formation of γ-Fe2O3 as well. By dynamic light scattering (DLS) method and zeta potential analyzer, the particle size distribution and stability of the systems were investigated. The magnetic behavior of the synthesized γ-Fe2O3 nanoparticles were studied using a vibrating sample magnetometer (VSM) which confirmed the ferrimagnetic particles with saturation magnetization of 54.94 emu/g. The resultant maghemite nanoparticles will be used in photocatalysts and humidity sensing. The net impact of the work stated here is based on the principle of converting waste into useful nanomaterials. Finally, it was concluded that our results can give insights into the design of the synthesis procedure from the precursor to the high-quality gamma iron oxide nanoparticles with high saturation magnetization for different potential applications which are inexpensive and very simple.

Ligands play a critical role in the optical properties and chemical stability of colloidal nanocrystals (NCs), but identifying ligands that can enhance NC properties is daunting, given the high dimensionality of chemical space. Here, we use machine learning (ML) and robotic screening to accelerate the discovery of ligands that enhance the photoluminescence quantum yield (PLQY) of CsPbBr3 perovskite NCs. We developed a ML model designed to predict the relative PL enhancement of perovskite NCs when coordinated with a ligand selected from a pool of 29,904 candidate molecules. Ligand candidates were selected using an active learning (AL) approach that accounted for uncertainty quantified by twin regressors. After eight experimental iterations of batch AL (corresponding to 21 initial and 72 model-recommended ligands), the uncertainty of the model decreased, demonstrating an increased confidence in the model predictions. Feature importance and counterfactual analyses of model predictions illustrate the potential use of ligand field strength in designing PL-enhancing ligands. Our versatile AL framework can be readily adapted to screen the effect of ligands on a wide range of colloidal nanomaterials.